from tensorflow  import keras

model = keras.Sequential([
    # 输入层   正常卷积 改变通道数 
    keras.layers.Conv2D(32,(3,3),strides=1,padding='same',activation='relu',input_shape=(28,28,1)), 
    keras.layers.BatchNormalization(),

    # 分离卷积层 效果和普通卷积一样 参数量少
    keras.layers.SeparableConv2D(32,(3,3),strides=1,padding='same',activation='relu'),  
    keras.layers.BatchNormalization(),

    # maxpooling层  改变大小
    keras.layers.MaxPool2D(pool_size=(2,2)),  

    # 堆叠: (分离卷积层+maxpooling层) x  n
    # fc层
    keras.layers.Flatten(),
    keras.layers.Dense(1,activation='softmax'),
])

model.summary()